Deep neural networks (DNNs) with their dense and complex algorithms
provide real possibilities for Artificial General Intelligence
(AGI). Meta-learning with DNNs brings AGI much closer: artificial
agents solving intelligent tasks that human beings can achieve,
even transcending what they can achieve. Meta-Learning: Theory,
Algorithms and Applications shows how meta-learning in combination
with DNNs advances towards AGI. Meta-Learning: Theory, Algorithms
and Applications explains the fundamentals of meta-learning by
providing answers to these questions: What is meta-learning?; why
do we need meta-learning?; how are self-improved meta-learning
mechanisms heading for AGI ?; how can we use meta-learning in our
approach to specific scenarios? The book presents the background of
seven mainstream paradigms: meta-learning, few-shot learning, deep
learning, transfer learning, machine learning, probabilistic
modeling, and Bayesian inference. It then explains important
state-of-the-art mechanisms and their variants for meta-learning,
including memory-augmented neural networks, meta-networks,
convolutional Siamese neural networks, matching networks,
prototypical networks, relation networks, LSTM meta-learning,
model-agnostic meta-learning, and the Reptile algorithm. The book
takes a deep dive into nearly 200 state-of-the-art meta-learning
algorithms from top tier conferences (e.g. NeurIPS, ICML, CVPR,
ACL, ICLR, KDD). It systematically investigates 39 categories of
tasks from 11 real-world application fields: Computer Vision,
Natural Language Processing, Meta-Reinforcement Learning,
Healthcare, Finance and Economy, Construction Materials, Graphic
Neural Networks, Program Synthesis, Smart City, Recommended
Systems, and Climate Science. Each application field concludes by
looking at future trends or by giving a summary of available
resources. Meta-Learning: Theory, Algorithms and Applications is a
great resource to understand the principles of meta-learning and to
learn state-of-the-art meta-learning algorithms, giving the
student, researcher and industry professional the ability to apply
meta-learning for various novel applications.
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